Background: Large for gestational age infants (LGA) have increased risk of adverse short-term perinatal outcomes. This study aims to develop a multivariable prediction model for the risk of giving birth to a LGA baby, by using biochemical, biophysical, anamnestic, and clinical maternal characteristics available at first trimester. Methods: Prospective study that included all singleton pregnancies attending the first trimester aneuploidy screening at the Obstetric Unit of the University Hospital of Modena, in Northern Italy, between June 2018 and December 2019. Results: A total of 503 consecutive women were included in the analysis. The final prediction model for LGA, included multiparity (OR = 2.8, 95% CI: 1.6–4.9, p = 0.001), pre-pregnancy BMI (OR = 1.08, 95% CI: 1.03–1.14, p = 0.002) and PAPP-A MoM (OR = 1.43, 95% CI: 1.08–1.90, p = 0.013). The area under the ROC curve was 70.5%, indicating a satisfactory predictive accuracy. The best predictive cut-off for this score was equal to − 1.378, which corresponds to a 20.1% probability of having a LGA infant. By using such a cut-off, the risk of LGA can be predicted in our sample with sensitivity of 55.2% and specificity of 79.0%. Conclusion: At first trimester, a model including multiparity, pre-pregnancy BMI and PAPP-A satisfactorily predicted the risk of giving birth to a LGA infant. This promising tool, once applied early in pregnancy, would identify women deserving targeted interventions. Trial registration: ClinicalTrials.gov NCT04838431, 09/04/2021.

A first trimester prediction model for large for gestational age infants: a preliminary study / Monari, F.; Menichini, D.; Spano' Bascio, L.; Grandi, G.; Banchelli, F.; Neri, I.; D'Amico, R.; Facchinetti, F.. - In: BMC PREGNANCY AND CHILDBIRTH. - ISSN 1471-2393. - 21:1(2021), pp. 654-662. [10.1186/s12884-021-04127-3]

A first trimester prediction model for large for gestational age infants: a preliminary study

Monari F.;Menichini D.;Grandi G.;Banchelli F.;Neri I.;D'Amico R.;Facchinetti F.
2021

Abstract

Background: Large for gestational age infants (LGA) have increased risk of adverse short-term perinatal outcomes. This study aims to develop a multivariable prediction model for the risk of giving birth to a LGA baby, by using biochemical, biophysical, anamnestic, and clinical maternal characteristics available at first trimester. Methods: Prospective study that included all singleton pregnancies attending the first trimester aneuploidy screening at the Obstetric Unit of the University Hospital of Modena, in Northern Italy, between June 2018 and December 2019. Results: A total of 503 consecutive women were included in the analysis. The final prediction model for LGA, included multiparity (OR = 2.8, 95% CI: 1.6–4.9, p = 0.001), pre-pregnancy BMI (OR = 1.08, 95% CI: 1.03–1.14, p = 0.002) and PAPP-A MoM (OR = 1.43, 95% CI: 1.08–1.90, p = 0.013). The area under the ROC curve was 70.5%, indicating a satisfactory predictive accuracy. The best predictive cut-off for this score was equal to − 1.378, which corresponds to a 20.1% probability of having a LGA infant. By using such a cut-off, the risk of LGA can be predicted in our sample with sensitivity of 55.2% and specificity of 79.0%. Conclusion: At first trimester, a model including multiparity, pre-pregnancy BMI and PAPP-A satisfactorily predicted the risk of giving birth to a LGA infant. This promising tool, once applied early in pregnancy, would identify women deserving targeted interventions. Trial registration: ClinicalTrials.gov NCT04838431, 09/04/2021.
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A first trimester prediction model for large for gestational age infants: a preliminary study / Monari, F.; Menichini, D.; Spano' Bascio, L.; Grandi, G.; Banchelli, F.; Neri, I.; D'Amico, R.; Facchinetti, F.. - In: BMC PREGNANCY AND CHILDBIRTH. - ISSN 1471-2393. - 21:1(2021), pp. 654-662. [10.1186/s12884-021-04127-3]
Monari, F.; Menichini, D.; Spano' Bascio, L.; Grandi, G.; Banchelli, F.; Neri, I.; D'Amico, R.; Facchinetti, F.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1266634
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